AIMC Topic: Dyspnea

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Automatic Detection of Dyspnea in Real Human-Robot Interaction Scenarios.

Sensors (Basel, Switzerland)
A respiratory distress estimation technique for telephony previously proposed by the authors is adapted and evaluated in real static and dynamic HRI scenarios. The system is evaluated with a telephone dataset re-recorded using the robotic platform de...

Dyspnea Severity Assessment Based on Vocalization Behavior with Deep Learning on the Telephone.

Sensors (Basel, Switzerland)
In this paper, a system to assess dyspnea with the mMRC scale, on the phone, via deep learning, is proposed. The method is based on modeling the spontaneous behavior of subjects while pronouncing controlled phonetization. These vocalizations were des...

Identification of Uncontrolled Symptoms in Cancer Patients Using Natural Language Processing.

Journal of pain and symptom management
CONTEXT: For patients with cancer, uncontrolled pain and other symptoms are the leading cause of unplanned hospitalizations. Early access to specialty palliative care (PC) is effective to reduce symptom burden, but more efficient approaches are neede...

Cardiorespiratory and metabolic demand of the 6-minute pegboard and ring test in healthy young adults.

Journal of bodywork and movement therapies
OBJECTIVE: To determine the cardiorespiratory and metabolic demand of the Six-Minute Pegboard and Ring Test (6PBRT) in healthy young adults and its association with maximal arm cycle ergometer test (arm CET).

Early detection of COVID-19 in the UK using self-reported symptoms: a large-scale, prospective, epidemiological surveillance study.

The Lancet. Digital health
BACKGROUND: Self-reported symptoms during the COVID-19 pandemic have been used to train artificial intelligence models to identify possible infection foci. To date, these models have only considered the culmination or peak of symptoms, which is not s...

App-based symptom tracking to optimize SARS-CoV-2 testing strategy using machine learning.

PloS one
BACKGROUND: Tests are scarce resources, especially in low and middle-income countries, and the optimization of testing programs during a pandemic is critical for the effectiveness of the disease control. Hence, we aim to use the combination of sympto...

Dyspnea, effort and muscle pain during exercise in lung transplant recipients: an analysis of their association with cardiopulmonary function parameters using machine learning.

Respiratory research
BACKGROUND: Despite improvement in lung function, most lung transplant (LTx) recipients show an unexpectedly reduced exercise capacity that could be explained by persisting peripheral muscle dysfunction of multifactorial origin. We analyzed the cours...

Identification of Risk Factors and Symptoms of COVID-19: Analysis of Biomedical Literature and Social Media Data.

Journal of medical Internet research
BACKGROUND: In December 2019, the COVID-19 outbreak started in China and rapidly spread around the world. Lack of a vaccine or optimized intervention raised the importance of characterizing risk factors and symptoms for the early identification and s...